The major approach of machine Learning is Dimensionality Reduction. Overriding of the learning model will be produced if the higher number of features applicable in the dataset. The medical records in various hospitals are high dimensional in nature, which produce poor performance. The techniques of Dimensionality Reduction are applicable to resolve the features and the dimensionality of data sets are reduced. For the design of various dimensional hospital data. The Linear and nonlinear methods of dimensionality Reduction techniques will be adapted and their ability is compared. Here the Kmeans Clustering algorithm is used.

Keywords : Machine Learning; Dimensionality Reduction (DR); Principal Component Analysis(PCA )